Conventionally, such inspections require the skill of an operator, who visually inspects the tire in order to detect possible defects visible on the surface of the latter. These operations are lengthy and expensive, and this is why manufacturers actively seek means for assisting the operator.
In this context, it proves necessary to acquire a digital representation of the relief of the surface of the tire to be inspected for the purpose, after analysis and processing, of comparing this digital representation with a reference image of the surface or with data coming from a model. This digital representation of the surface is also called the relief image of the surface.
More particularly, the invention relates to the field of the stereoscopic acquisition of a relief image of the surface.
Various image acquisition methods have been disclosed for the purpose of supplying data as relevant as possible to a digital processing means capable of comparing this image with a reference image so as to determine the conformity of the tire being analysed.
Using the technique of classical stereovision, it has been proposed to use two separate cameras dedicated respectively to the acquisition of data relating to the relief and to the acquisition of data relating to the appearance, such as the colour, greyscale or brightness.
This solution, called a passive stereoscopic solution, requires the images coming from the two acquisition means to be brought into correspondence. The correspondences may be determined using characteristic elements of the image, such as the presence of characteristic corners or contours. The coordinates of the surface are then calculated by triangulation by determining the angles of different views of the same point on the surface seen by the two cameras.
However, several assumptions are necessary in order for the calculation algorithms to be executed appropriately. This is because ambiguities may arise when the surface to be evaluated has areas of light reflection or refraction. In this case, the algorithms cannot correctly determine the correspondences between the pixels of the two cameras. In addition, unlike the human brain, they have no knowledge of the topography or context of the image to be analysed. It may therefore be necessary to involve an operator in the analysis process in order to select the points to be brought into correspondence.
Thus, in contrast to passive optical techniques, acquisition techniques referred to as active techniques have been developed that consist in sending an optical signal onto the surface to be reconstructed seen by cameras at different angles in order to make it easier to bring the points of the surface into correspondence.
These methods consist in illuminating the surface using known luminous features, which are sensed by the optical receivers of the cameras. The operation of bringing the images recorded by the two stereoscopic cameras into correspondence is facilitated by knowing the elements of the feature, and the abovementioned ambiguities are therefore resolved during the analysis.
As will be explained in greater detail later, one of the structured light projection algorithms most commonly used consists in illuminating the surface using light formed from a series of binary features made up of bands, comprising an alternation of illuminated lines and non-illuminated lines. At the same time, the cameras acquire these series of successive images in which each of the points on the surface may be illuminated or non-illuminated. It is then possible to reconstruct the alternation of illuminated and non-illuminated bands seen by the two cameras, to identify the light bands in a one-to-one manner in order to locate a point on the surface with certainty and to bring the images from the two cameras into correspondence so as to reconstruct the relief image of the surface.
Using these illumination algorithms judiciously, it is thus possible to acquire the image of the surface of a tire while avoiding the effects due to shadow areas when the relief of the surface is greatly cut-up, but also to provide sufficient information for an image processing means to distinguish the brightness effects due to stains or colour variations.
Application of the abovementioned methods to evaluating the relief of the surface of a tire may involve several adaptations when it is desired to optimize the image acquisition cycle, in particular when it is desired to define the relief of the tread.
FIG. 1 illustrates the case of a conventional application in which an illumination means 20 projects a fringe system onto the tread and in which stereoscopic cameras 10a and 10b are placed so as to acquire the light emitted (E) by the illumination means 20 and reflected (F) by the surface of the tire P. The tire is fitted onto the rim 30 of a wheel 31 rotated about the axis D by a motor-driven support hub 32.
At each acquisition pass, the cameras record the two stereoscopic images of an angular portion a of the surface of the tread. The complete image of the tread is obtained by making the tire rotate through one complete revolution about its axis of revolution D and butting together the 2π/α pictures taken by each of the stereoscopic cameras.
Implementation of the algorithm also requires fringe systems S of the type of those illustrated in FIGS. 2, 3 and 3a to be projected in succession one after another. The fringe systems comprise an alternation of illuminated and non-illuminated bands of known widths according to a binary code determined in advance (S1, S2, S3, S4) and are associated with encoding and decoding techniques enabling the fringes of the projected images, recorded by the cameras, to be identified.
The stereoscopic cameras acquire the images of the projection of each of the fringe systems S1, S2, S3 and then S4 in succession onto the surface of the tire.
Referring to FIGS. 3a and 3b, the fringe system S1 corresponds to the first row. The fringe system S2 corresponds to row 2, the fringe system S3 corresponds to row 3 and the fringe system S4 corresponds to row 4. The number of fringe systems that can be projected is of course not limiting.
A processing system, involving known algorithms (these not forming part of the present description), decodes the images in order to associate with each point on the surface of the tire the successive illumination levels so as to resolve any positioning uncertainties.
A first method therefore consists in projecting each of the fringe systems in succession onto a portion of the tire and then in repeating this operation on the successive angular sectors by rotating the tire about its axis. A second method consists in taking, for each fringe system, images over a complete revolution of the tire and in making as many revolutions as there are fringe systems to be projected.
Whatever the method chosen, it has been found that these successive revolutions take up a considerable amount of time and reduce the efficiency of the inspection system. Such solutions also require particularly precise coding and synchronization means.
To reduce the acquisition time it is then possible, as proposed in the publication U.S. Pat. No. 4,175,862, to place as many fringe projection devices, associated with stereoscopic image means for the acquisition of the digital relief image of the surface of a tire, as the number N of fringe systems to be projected.
In this way, it is possible to acquire the 2N images of the complete surface of a tire illuminated by the N fringe systems, coming from the 2N stereoscopic cameras, by making the tire undergo a single revolution about its axis of revolution.
However, such a device requires a large number of cameras and projectors, which may interfere with one another and may have in addition the drawback of entailing many additional calculations in order to bring the N relief images of the surface into registration one with respect to another.